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Greedy Randomized Adaptive Search Procedures
, 2002
"... GRASP is a multistart metaheuristic for combinatorial problems, in which each iteration consists basically of two phases: construction and local search. The construction phase builds a feasible solution, whose neighborhood is investigated until a local minimum is found during the local search phas ..."
Abstract

Cited by 648 (82 self)
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GRASP is a multistart metaheuristic for combinatorial problems, in which each iteration consists basically of two phases: construction and local search. The construction phase builds a feasible solution, whose neighborhood is investigated until a local minimum is found during the local search
Search procedures and parallelism in constraint programming
 In Proc. of CP99
, 1999
"... Abstract. In this paper, we present a major improvement in the search procedures in constraint programming. First, we integrate various search procedures from AI and OR. Second, we parallelize the search on sharedmemory computers. Third, we add an objectoriented extensible control language to impl ..."
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Cited by 46 (4 self)
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Abstract. In this paper, we present a major improvement in the search procedures in constraint programming. First, we integrate various search procedures from AI and OR. Second, we parallelize the search on sharedmemory computers. Third, we add an objectoriented extensible control language
TABU SEARCH
"... Tabu Search is a metaheuristic that guides a local heuristic search procedure to explore the solution space beyond local optimality. One of the main components of tabu search is its use of adaptive memory, which creates a more flexible search behavior. Memory based strategies are therefore the hallm ..."
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Cited by 819 (48 self)
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Tabu Search is a metaheuristic that guides a local heuristic search procedure to explore the solution space beyond local optimality. One of the main components of tabu search is its use of adaptive memory, which creates a more flexible search behavior. Memory based strategies are therefore
The EvolutionaryGradientSearch Procedure
 Genetic Programming 1998: Proceedings of the Third Annual Conference
"... Abstract. The pertinent literature controversially discusses in which respects evolutionary algorithms differ from classical gradient methods. This chapter presents a hybrid, called the evolutionarygradientsearch procedure, that uses evolutionary variations to estimate the gradient direction in w ..."
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Cited by 1 (1 self)
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Abstract. The pertinent literature controversially discusses in which respects evolutionary algorithms differ from classical gradient methods. This chapter presents a hybrid, called the evolutionarygradientsearch procedure, that uses evolutionary variations to estimate the gradient direction
Induction as a Search Procedure
"... 1 Induction as a Search Procedure This chapter introduces Inductive Logic Programming from the perspective of search algorithms in Computer Science. It first briefly considers the Version Spaces approach to induction, and then focuses on Inductive Logic Programming: from its formal definition and ..."
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1 Induction as a Search Procedure This chapter introduces Inductive Logic Programming from the perspective of search algorithms in Computer Science. It first briefly considers the Version Spaces approach to induction, and then focuses on Inductive Logic Programming: from its formal definition
A New Method for Solving Hard Satisfiability Problems
 AAAI
, 1992
"... We introduce a greedy local search procedure called GSAT for solving propositional satisfiability problems. Our experiments show that this procedure can be used to solve hard, randomly generated problems that are an order of magnitude larger than those that can be handled by more traditional approac ..."
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Cited by 730 (21 self)
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We introduce a greedy local search procedure called GSAT for solving propositional satisfiability problems. Our experiments show that this procedure can be used to solve hard, randomly generated problems that are an order of magnitude larger than those that can be handled by more traditional
Search Procedures in High Energy Physics
"... Abstract The usual procedure for searching for new phenomena in high energy physics involves a frequentist hypothesis test followed by the construction of an interval for the parameter of interest. This procedure has a couple of wellknown flaws: the effect of the test on subsequent inference is ig ..."
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Abstract The usual procedure for searching for new phenomena in high energy physics involves a frequentist hypothesis test followed by the construction of an interval for the parameter of interest. This procedure has a couple of wellknown flaws: the effect of the test on subsequent inference
Ant Colony System: A cooperative learning approach to the traveling salesman problem
 IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
, 1997
"... This paper introduces the ant colony system (ACS), a distributed algorithm that is applied to the traveling salesman problem (TSP). In the ACS, a set of cooperating agents called ants cooperate to find good solutions to TSP’s. Ants cooperate using an indirect form of communication mediated by a pher ..."
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Cited by 1037 (53 self)
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ACS3opt, a version of the ACS augmented with a local search procedure, to some of the best performing algorithms for symmetric and asymmetric TSP’s.
Greedy Randomized Adaptive Search Procedures For The Steiner Problem In Graphs
 QUADRATIC ASSIGNMENT AND RELATED PROBLEMS, VOLUME 16 OF DIMACS SERIES ON DISCRETE MATHEMATICS AND THEORETICAL COMPUTER SCIENCE
, 1999
"... We describe four versions of a Greedy Randomized Adaptive Search Procedure (GRASP) for finding approximate solutions of general instances of the Steiner Problem in Graphs. Di#erent construction and local search algorithms are presented. Preliminary computational results with one of the versions ..."
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Cited by 122 (31 self)
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We describe four versions of a Greedy Randomized Adaptive Search Procedure (GRASP) for finding approximate solutions of general instances of the Steiner Problem in Graphs. Di#erent construction and local search algorithms are presented. Preliminary computational results with one
Coping with errors in binary search procedures
, 1980
"... We consider the problem of identifying an unknown value x E (1, Z,..., n} using only comparisons of x to constants when as many as E of the comparisons may receive erroneous answers. For a continuous analogue of this problem we show that there is a unique strategy that is optimal in the worst case. ..."
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Cited by 18 (0 self)
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of this search problem with errors is equivalent to the problem of finding the minimal root of a set of increasing functions. The modified version is then also shown to be of complexity logsn + E. logslogsn + O(E * log&).
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